This thesis conducted an operational analysis to inform the designs of future mine countermeasures (MCM) ships. This was primarily focused on identifying the ship design characteristics that will have the largest impact on mine detection and classification. The research developed a systems architecture, operational model, and related analysis to interpret results, draw conclusions, and make recommendations. An agent-based model was developed to simulate four different MCM scenarios in which an MCM surface vessel searched a designated area that contained 32 potential mines. For each of the four scenarios, ship design characteristics were varied to determine which variables had the greatest impact on performance. To determine how well each design performed, the data was analyzed against two different measures of effectiveness (MOE): the average number of mines accurately detected and classified (MOE #1), and the average number of timesteps required to achieve mission success (MOE #2). The study found that improving the ship speed and reducing the detection delay has a large impact on performance in the scenarios where there is no unmanned underwater vehicle (UUV) present. It also found that limiting the deployment range of the UUV is of paramount importance in the scenarios where there is a UUV present.

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